Provably Optimal and Human-Competitive Results in SBSE for Spectrum Based Fault Localisation

@InProceedings{Xie:2013:SSBSE,
author = "Xiaoyuan Xie and Fei-Ching Kuo and Tsong Yueh Chen and
Shin Yoo and Mark Harman",
title = "Provably Optimal and Human-Competitive Results in SBSE
for Spectrum Based Fault Localisation",
booktitle = "Symposium on Search-Based Software Engineering",
year = "2013",
editor = "Guenther Ruhe and Yuanyuan Zhang",
volume = "8084",
series = "Lecture Notes in Computer Science",
pages = "224--238",
address = "Leningrad",
month = aug # " 24-26",
publisher = "Springer",
keywords = "genetic algorithms, genetic programming, SBSE",
isbn13 = "978-3-642-39741-7",
URL = "http://www.cs.ucl.ac.uk/staff/s.yoo/papers/Xie2013kx.pdf",
DOI = "doi:10.1007/978-3-642-39742-4_17",
size = "15 pages",
abstract = "Fault localisation uses so-called risk evaluation
formulae to guide the localisation process. For more
than a decade, the design and improvement of these
formulae has been conducted entirely manually through
iterative publication in the fault localisation
literature. However, recently we demonstrated that SBSE
could be used to automatically design such formulae by
recasting this as a problem for Genetic Programming
(GP). In this paper we prove that our GP has produced
four previously unknown globally optimal formulae.
Though other human competitive results have previously
been reported in the SBSE literature, this is the first
SBSE result, in any application domain, for which human
competitiveness has been formally proved. We also show
that some of these formulae exhibit counter-intuitive
characteristics, making them less likely to have been
found solely by further human effort.",
notes = "See also Technical Report RN/14/14
http://www.cs.ucl.ac.uk/fileadmin/UCL-CS/research/Research_Notes/rn-14-14.pdf",
}